IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/8784065.html
   My bibliography  Save this article

Slot Machine RTP Optimization Using Variable Neighborhood Search

Author

Listed:
  • Pantelis-Arsenios Kamanas
  • Angelo Sifaleras
  • Nikolaos Samaras

Abstract

This work presents a Variable Neighborhood Search (VNS) approach for solving the Return-To-Player (RTP) optimization problem. A large number of software companies in the gaming industry seek to solve the RTP optimization problem in order to develop modern virtual casino gambling machines. These slot machines have a number of reels (e.g., three or more) that spin once a button is pushed. Each slot machine is required to have an RTP in a particular range according to the legislation of each country. By using a VNS framework that guides two local search operators, we show how to control the distribution of the symbols in the reels in order to achieve the desired RTP. In this study, optimization refers only to base game, the core of slot machine games, and not in bonus games, since a bonus game is triggered once two, three, or more specific symbols occur in the gaming monitor. Although other researchers have tried to solve the RTP problem in the past, this is the first time that a VNS methodology is proposed for this problem in the literature with good computational results.

Suggested Citation

  • Pantelis-Arsenios Kamanas & Angelo Sifaleras & Nikolaos Samaras, 2021. "Slot Machine RTP Optimization Using Variable Neighborhood Search," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-8, May.
    • Handle: RePEc:hin:jnlmpe:8784065
    DOI: 10.1155/2021/8784065
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/MPE/2021/8784065.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/MPE/2021/8784065.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2021/8784065?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Slavi Georgiev & Venelin Todorov, 2023. "Efficient Monte Carlo Methods for Multidimensional Modeling of Slot Machines Jackpot," Mathematics, MDPI, vol. 11(2), pages 1-18, January.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hin:jnlmpe:8784065. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.